[SciPy-user] Question about scipy.optimize

[Alan G Isaac]

If I understand what you sent, you are trying to
turn a constrained minimization into an unconstrained
minimization by introducing a Lagrange multiplier.
This does not work: the first order conditions
associated with L characterize a saddle.

However in your case you can simply solve 2*x*x+y*y=3
for y (only the bottom half of the ellipse is relevant)
and substitute this into x*x*y to get an unconstrained
optimization problem in x.  Naturally it will not have a
unique solution, since x occurs only as x*x.  However
the resulting function is convex local to the minima,
so you should then be able to use scipy.optimize.

Cheers,
Alan Isaac